Attribute and Scale Selection Based on Test Cost in Consistent Multi-scale Decision Systems

被引：0
作者：
Wu D. [1 ,2 ,3 ,4 ]
Liao S. [1 ,2 ,3 ,4 ]
Fan Y. [1 ,2 ,3 ,4 ]
机构：
[1] School of Mathematics and Statistics, Minnan Normal University, Zhangzhou
[2] Fujian Key Laboratory of Granular Computing and Application, Minnan Normal University, Zhangzhou
[3] Institute of Meteorological Big Data-Digital Fujian, Minnan Normal University, Zhangzhou
[4] Fujian Key Laboratory of Data Science and Statistics, Minnan Normal University, Zhangzhou
来源：
Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence | 2023年 / 36卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Attribute and Scale Selection; Monotonicity; Multi-scale Decision System; Test Cost;
D O I：
10.16451/j.cnki.issn1003-6059.202305004
中图分类号：
学科分类号：
摘要：
The processing of multi-scale decision systems can simplify the complex problem, and simultaneous selection of attributes and scales is an important method in this process. In addition, the influence of cost factors is often taken into consideration in practical data processing. However, there is no research on cost factors in the simultaneous selection of attributes and scales. To solve this problem, the method of attribute and scale selection based on test cost in consistent multi-scale decision systems is proposed in this paper. Firstly, a corresponding rough set theoretical model is constructed. Both attribute and scale are considered in definitions and properties of the constructed theoretical model, and the test cost-based attribute-scale significance function is provided. Then, on the basis of concepts and properties of rough set applicable to multi-scale decision systems, a heuristic algorithm for simultaneous selection of attributes and scales is proposed. Experiments on UCI dataset show that the proposed algorithm significantly reduces the total test cost and improves computational efficiency. © 2023 Journal of Pattern Recognition and Artificial Intelligence. All rights reserved.
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页码：433 / 447
页数：14
相关论文
共 27 条
  • [1] PAWLAK Z., Rough Sets, International Journal of Computer and Information Sciences, 11, 5, pp. 341-356, (1982)
  • [2] LUO G Z, YANG X B., Limited Dominance-Based Rough Set Model and Knowledge Reductions in Incomplete Decision System, Journal of Information Science and Engineering, 26, 6, pp. 2199-2211, (2010)
  • [3] WU W Z, LEUNG Y., Theory and Applications of Granular Labelled Partitions in Multi-scale Decision Tables, Information Sciences, 181, 18, pp. 3878-3897, (2011)
  • [4] WU W Z, LEUNG Y., Optimal Scale Selection for Multi-scale Decision Tables, International Journal of Approximate Reasoning, 54, 8, pp. 1107-1129, (2013)
  • [5] LI F, HU B Q., A New Approach of Optimal Scale Selection to Multi-scale Decision Tables, Information Sciences, 381, pp. 193-208, (2017)
  • [6] LI F, HU B Q, WANG J., Stepwise Optimal Scale Selection for Multi-scale Decision Tables via Attribute Significance, Knowledge-Based Systems, 129, pp. 4-16, (2017)
  • [7] LI J H, HE J J., Uncertainty Measurement and Optimal Granularity Selection for Multi-granularity Formal Context, Control and Decision, 37, 5, pp. 1299-1308, (2022)
  • [8] CHEN Y S, LI J H, LI J J, Et al., Sequential 3WD-Based Local Optimal Scale Selection in Dynamic Multi-scale Decision Information Systems, International Journal of Approximate Reasoning, 152, pp. 221-235, (2023)
  • [9] ZHU Y J, YANG B., Optimal Scale Combination Selection for Inconsistent Multi-scale Decision Tables, Soft Computing, 26, 13, pp. 6119-6129, (2022)
  • [10] YANG X, HUANG B., Optimal Scale Selection and Reduction of Decision-Theoretic Rough Set Based on Fuzzy Similarity Relation in Multi-scale Decision Systems, Journal of Nanjing University of Science and Technology, 45, 4, pp. 455-463, (2021)
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